Anthony Goldbloom is the founder and CEO of Kaggle. In 2011 & 2012, Forbes Magazine named Anthony as one of the 30 under 30 in technology. In 2011, Fast Company featured him as one of the innovative thinkers who are changing the future of business.
He and Lukas discuss the differences in strategies that do well in Kaggle competitions vs academia vs in production. They discuss his 2016 Ted talk through the lens of 2020, frameworks, and languages.

Topics Discussed:
0:00 Sneak Peek
0:20 Introduction
0:45 methods used in kaggle competitions vs mainstream academia
2:30 Feature engineering
3:55 Kaggle Competitions now vs 10 years ago
8:35 Data augmentation strategies
10:06 Overfitting in Kaggle Competitions
12:53 How to not overfit
14:11 Kaggle competitions vs the real world
18:15 Getting into ML through Kaggle
22:03 Other Kaggle products
25:48 Favorite under appreciated kernel or dataset
28:27 Python & R
32:03 Frameworks
35:15 2016 Ted talk though the lens of 2020
37:54 Reinforcement Learning
38:43 What’s the topic in ML that people don’t talk about enough?
42:02 Where are the biggest bottlenecks in deploying ML software?

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We started Weights and Biases to build tools for Machine Learning practitioners because we care a lot about the impact that Machine Learning can have in the world and we love working in the trenches with the people building these models. One of the most fun things about these building tools has been the conversations with these ML practitioners and learning about the interesting things they’re working on. This process has been so fun that we wanted to open it up to the world in the form of our new podcast called Gradient Dissent. We hope you have as much fun listening to it as we had making it!

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Host: Lukas Biewald - https://twitter.com/l2k

Producer: Lavanya Shukla - https://twitter.com/lavanyaai

Editor: Cayla Sharp - http://caylasharp.com/